One fully funded, 3 year PhD studentship in Statistics is available at the University of Strathclyde Mathematics and Statistics department to a highly motivated UK or EU student. The studentship will be formally aligned with the STRADDLE DTC, a centre of excellence in the linkage and analysis of data across disciplines. Along with the core students of the DTC, the student on this project will be trained to be part of the next generation of data scientists.
Aims and objectives: The objectives of this studentship are (i) to develop statistical methods to analyse linked individual and spatial data and (ii) to provide a comprehensive analysis of the development of social inequalities over time and geographical area using data from the Child Mental Health in Education (ChiMe) study, on 90,000 children aged 4 to 10 years followed up for between 2 and 6 years.
Background: Social, emotional and behavioural development in early to middle childhood has enormous impact across the lifespan. Problems with early development can be associated with early pregnancy, poor school achievement, problems with employment and relationships in adulthood, and poor physical and mental health. Home, neighbourhood and school environments are important contributors to childhood development. While individual level contributors such as poverty and parenting still have the largest impact, area level factors such as neighbourhood deprivation, violence and local service provision play a substantial part.
Data: The ChiME study https://www.gla.ac.uk/researchinstitutes/healthwellbeing/research/mentalhealth/research/projects/chime/
) is a collaboration between the Universities of Glasgow, Aberdeen, Strathclyde, Edinburgh and Glasgow City Council Education Services. Goodman’s Strengths and Difficulties Questionnaire (SDQ) was completed for all children in state education in Glasgow City in pre-school (4-5 years), primary 3 (6-7 years) and primary 6 (9-10 years) from 2009 to 2016 inclusive and linked to the children’s demographic characteristics.
Statistical Methods: Previous developments in spatial analysis focus on outcomes such as counts of people with a particular disease in a particular area and so are purely aggregated spatial data. The individuals in the ChiME dataset have scores at an individual level, so the outcome variable is profoundly different and leads to different interpretation. Initial models for combining individual and area level data have been developed that allow for correlated covariates but not for spatial correlation between individuals. The student will be required to develop statistical models for the analysis of repeated individual and area level data within a spatiotemporal geography, where individuals can move from one geographical unit to another.
The project will address how to appropriately model the individual level SDQ scores, while adjusting for and assessing the impact of individual and area level covariates, and how to account for demographic characteristics that cannot be changed, such as assigned sex at birth, and those that potentially can, such as age of entry at school and area-level deprivation. It will investigate how to assess the relative impact of demographic and spatial effects and will extend the previous work to include the temporal aspect of the complete dataset to study how area impacts and social inequalities change as children get older. It will assess and adjust for spatial correlation for different small area sizes, such as local datazones and larger electoral wards and how best to ensure a balance between comprehensive use of information and policy impact. It will consider children who move house within the city to assess whether, on average, their scores change in accordance with the overall performance of their new local area.
How to Apply: Applicants must have obtained, or expect to obtain, a first or 2.1 UK honours degree, or equivalent for degrees obtained outside the UK, in a quantitative discipline. Please direct all enquiries and applications to [email protected]
. Applications will be reviewed when received, shortlisted candidates will be invited to interview on a rolling basis and it is anticipated that the PhD Studentship will start in October 2019. The application process will remain open until the position is filled. All applications must be submitted via email (subject line: PhD applicant – University of Strathclyde ChiME) as a single pdf file and include the following:
A cover letter (max 1 page) explaining your interest and fit to the project; and
A CV (maximum three pages).